> MANOJ KUMAR N

[ Ethical Hacker & Security Analyst ]

Penetrating systems. Defending networks. Securing the future.

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> whoami

> System Status: Active

> Location: Bengaluru, Karnataka, India

> Education: MCA Graduate

Transitioning from financial operations to offensive security, I bring analytical precision and systematic problem-solving to cybersecurity. I specialize in penetration testing, vulnerability assessment, and network security analysis.

My research in deep reinforcement learning for radio resource management under DoS attacks demonstrates my commitment to advancing cybersecurity through innovative approaches. Currently mastering CEH v13 and CEH v13 AI methodologies to stay at the cutting edge of offensive security.

> Mission: Identify vulnerabilities before adversaries do. Secure digital infrastructures through proactive defense and ethical exploitation.

1
IEEE Publication
2+
Years in Tech
∞
Lines of Code
100%
Ethical Approach

> arsenal --list

[ Penetration Testing ]

  • Burp Suite
  • Metasploit Framework
  • Nmap
  • SQLMap
  • OWASP ZAP

[ Network Security ]

  • Wireshark
  • Nessus
  • Snort
  • TCP/IP Analysis
  • Firewall Configuration

[ Programming ]

  • Python
  • Bash Scripting
  • JavaScript
  • PHP
  • SQL

[ Operating Systems ]

  • Kali Linux
  • Parrot Security OS
  • Windows
  • Ubuntu Server
  • Virtual Environments

[ Cryptography ]

  • SSL/TLS Analysis
  • Hash Cracking
  • Encryption Methods
  • PKI Infrastructure
  • Digital Forensics

[ Additional Skills ]

  • OSINT Techniques
  • Social Engineering
  • Vulnerability Assessment
  • Security Auditing
  • Incident Response

> research --publications

A Novel Abstraction Framework for Efficient Radio Resource Management Using Deep Reinforcement Learning

Conference: 2025 5th International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT)
Publisher: IEEE | Year: 2025
Abstract: This paper gives a complete framework that combines deep reinforcement learning algorithms with advanced methods for modeling abstract state spaces to solve these problems in the best way possible. We use a Markov Decision Process to define the resource allocation problem and come up with new ways to group things, such as uniform, similarity-based, and dissimilarity-based strategies. The proposed method utilizes Deep Q-Networks and Actor-Critic techniques to enhance resource allocation decisions while adhering to quality of service standards. Extensive simulations reveal that our abstract model performs nearly optimally with greatly diminished computational complexity, making it appropriate for real-time implementation in dynamic wireless settings.
Read Paper DOI Link Conference Proceedings

> projects --showcase

Penetration Testing Labs

Custom-built virtual environments for practicing exploitation techniques and vulnerability assessments.

[ COMING SOON ]

Network Scanner Tool

Automated network reconnaissance tool built with Python for identifying vulnerabilities and open ports.

[ COMING SOON ]

Web Vulnerability Scanner

Custom web application security scanner focusing on OWASP Top 10 vulnerabilities detection.

[ COMING SOON ]

CTF Writeups

Documentation of Capture The Flag challenges, exploitation techniques, and security analysis.

[ COMING SOON ]

Malware Analysis Lab

Isolated environment for reverse engineering and behavioral analysis of malicious software.

[ COMING SOON ]

Wireless Security Suite

Collection of tools and scripts for auditing wireless networks and detecting security weaknesses.

[ COMING SOON ]

> contact --init

> Let's collaborate on securing digital infrastructures. Available for penetration testing, security audits, and cybersecurity consulting.

Email dev@maanoj.com
LinkedIn linkedin.com/in/maanoj
GitHub github.com/ManoJ-46
Location Bengaluru, Karnataka